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GPT Neo 1.3B Dutch by yhavinga

 »  All LLMs  »  yhavinga  »  GPT Neo 1.3B Dutch   URL Share it on

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  Autotrain compatible Dataset:yhavinga/mc4 nl cleane...   Endpoints compatible   Gpt-neo   Gpt-neo-1.3b   Gpt neo   Jax   Nl   Pytorch   Region:us   Safetensors   Tensorboard
Model Card on HF 🤗: https://huggingface.co/yhavinga/gpt-neo-1.3B-dutch 

GPT Neo 1.3B Dutch Benchmarks

LLME Score: 0.001
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
GPT Neo 1.3B Dutch (yhavinga/gpt-neo-1.3B-dutch)
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GPT Neo 1.3B Dutch Parameters and Internals

Model Type 
text generation
Additional Notes 
This project was supported by Google TPU Research Cloud and utilized HuggingFace tools extensively.
Supported Languages 
Dutch (native)
Training Details 
Data Sources:
cleaned Dutch mC4
Data Volume:
33B tokens
Methodology:
Trained from scratch for Dutch
Context Length:
512
Training Time:
7 days 11 hours
Hardware Used:
Google TPU through TPU Research Cloud
Model Architecture:
GPT-Neo, similar to GPT-3 but open-source
Input Output 
Input Format:
Text
Accepted Modalities:
text
Output Format:
Generated text
Release Notes 
Version:
1.3B
Notes:
Initial release of the Dutch GPT-Neo model with 1.3 billion parameters.
LLM NameGPT Neo 1.3B Dutch
Repository 🤗https://huggingface.co/yhavinga/gpt-neo-1.3B-dutch 
Model Size1.3b
Required VRAM5.4 GB
Updated2025-09-23
Maintaineryhavinga
Model Typegpt_neo
Model Files  5.4 GB   5.4 GB
Supported Languagesnl
Model ArchitectureGPTNeoForCausalLM
Context Length2048
Model Max Length2048
Transformers Version4.13.0
Tokenizer ClassGPT2Tokenizer
Vocabulary Size50257
Torch Data Typefloat32
Activation Functiongelu_new

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Note: green Score (e.g. "73.2") means that the model is better than yhavinga/gpt-neo-1.3B-dutch.

Rank the GPT Neo 1.3B Dutch Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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Release v20241124
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